Inexpensive fixed-point cameras may be called webcams and, as frequently used for capturing vehicles on roads, are useful as a “virtual sensor” providing vehicle volume and velocity observations. A variety of webcam-based Internet sites offer real-time traffic images to help motorists and other stakeholders. Typically such cameras are subject to small movements by a variety of forces such as wind and rain, birds landing on the camera, etc. Therefore even though such webcams are considered fixed-point cameras, the image on any given day/time may be slightly different from the intended or original image. Furthermore, due to the inexpensive nature of such cameras, new webcams are constantly being added to the Internet. Indexing and maintaining a library of every available camera and the roads that are targeted by the same has proven difficult. Unfortunately, image analysis requires fine tuning for identifying roads in captured images, and such analysis is often therefore impractical.
Content-based image retrieval techniques use the image features of color, texture, edges, etc. in an affine-transformation-robust manner. They cannot, however, be of use for detecting how to transform a captured image to match each road in the image to roads in a map. Furthermore such techniques are not tolerant to general projection transformation including keystone effects, in addition to scaling, rotation, and skews. Improved methods of processing web cam images therefore remains desirable.